Recent results from a collaboration between IBM Quantum, IBM Research Europe–Zurich, Los Alamos National Laboratory, and Zuse Institute Berlin have been published in the Nature Computational Science special issue on the year of quantum and have been highlighted on the cover page. The article, “Quantum Approximate Multi-Objective Optimization” by Ayse Kotil, Elijah Pelofske, Stephanie Riedmüller, Daniel J. Egger, Stephan Eidenbenz, Thorsten Koch, and Stefan Woerner demonstrates the potential of quantum computers for solving multi-objective optimization problems. Combining the quantum approximate optimization algorithm (QAOA) with the classical weighted sum method not only finds unsupported solutions that can not be recovered by classical weighted sum approaches but also shows an unexpectedly successful application of parameter transfer.
